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Dyadic Analysis: Using HLM David A. Kenny University of Connecticut /

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Types of Dyads Definitions Distinguishable Dyads with a categorical within-dyads variables that makes a difference e. g., parent-child Indistinguishable Ordering of the two members is arbitrary e.g. roommates Whether dyads are distinguishable or not is matter of theoretical and statistical considerations.

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Nonindependence: Definition l Degree of greater similarity (or dissimilarity) between linked observations versus unlinked observations l Nonindependence as the correlation between linked observations.

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Negative Nonindependence l Two scores from the same dyad are more dissimilar than two scores from different groups. l How?

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§Compensation: If one person has a large score, the other person lowers his or her score. For example, if one person acts very friendly, the partner may distance him or herself, §Social comparison: The members of the dyad use the relative difference on some measure to determine some other variable. For instance, satisfaction after a tennis match is determined by the score of that match. §Zero-sum: The sum of two scores is the same for each dyad. For instance, the two members divide a reward that is the same for all dyads. §Division of labor: Dyad members assign one member to do one task and the other member to do another. For instance, the amount of housework done in the household may be negatively correlated.

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Dyadic Designs l Standard l Each person has one partner l Social Relations Model (SRM) Designs l Each person has many partners, and each partner paired with many persons l One-with-Many l Each person has many partners, but each partner is paired with only one person

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Standard Design

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One-with-Many Design

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SRM Designs

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Remaining part of the presentation focuses on the standard design which is used in most dyadic studies.

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Dyadic Data Organization l Individual l One record for each individual l Only that individuals data on the record l Dyad (useful for distinguishable dyads) l Each record one dyad l Different variables for each person l Pairwise (useful for distinguishable dyads) l One record for each person l The persons data and partner data included (each data point included twice)

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Pairwise Data Organization l Dyad Number l Member Number l The Persons Data l Partners Data l Acitelli Example Acitelli Example

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Types of Variables Between Dyads – Level Two Both members have the same score X = X Within Dyads Sum of two scores a constant X + X = c for all dyads

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Mixed Variables l Variables that vary within and between groups l Examples Most outcomes (and mediators) Individual differences (e.g., personality)

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Gender and the Three Types Between Gay and Lesbian Couples Within Heterosexual Married Couples Mixed Friends

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Actor-Partner Interdependence Model

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Types of APIM Models actor only a > 0; p = 0 partner only p > 0; a = 0 couple model a = p social comparison model a + p = 0

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Actor-Partner Interaction Partner effect depends on the level of the actor effect More than one way to test A Level 2 Variable

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Measurement of the Actor-Partner Interaction Standard Product Approach (XX) – make sure variables centered Discrepancy Score (X – X) (Absolute Difference) Similarity – Negative Coefficient Dissimilarity – Positive Coefficient Higher Score of the Two [Max(X,X )] – It Takes Two Lower Score [Min(X,X )] – One of Us Can Drag Us Both Down

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Estimation Indistinguishable Members Multilevel Modeling Pairwise Data File Illustrate with HLM Distinguishable Members Structural Equation Modeling Dyad Data File

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Approaches Illustrated Conventional Multilevel Model with Random Intercepts Two-Intercept Model

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Briefly Discussed One-with-many design Standard design studied longitudinally

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